Bibliographic record
Abstract
The new linguistic science lacunology has come into prominence recently. The lacunae studies embrace sociolinguistics, nonverbal semiotics and applied linguistics studies. The re-search of terms of lacunology (lacunicon) is devoted to empty places in the structure of the contrasting languages and the ways of zero verbalization in the written and oral discourse. The empty category of the category “lacunarity” has been studied by the Canadian transla-tors Jean Paul Vinay (1910-1999) and Jean Darbelnet (1904-1990), the Russian pioneers of lacu-nology Yuriy Sorokin (1936-2009) and Gulchera Bikova and their followers. The research has resulted in the cognitive mind mapping. It turned out that lacunarity has several vectors, e.g. lacunae of language (i), lacunae of speech (ii), lacunae of cognition (iii) to be further discussed in the article. The basic terms of lacunicon are described. These are a pause in syntagmatics, a linguistic gap in paradigmatics, a lacuna in both diachronic and synchronic regimes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.037 |
| Scholarly communication | 0.009 | 0.025 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".